Adaptation and Learning in Multi-Agent Systems

IJCAI' 95 Workshop, Montreal, Canada, August 21, 1995. Proceedings.

AvGerhard Weiß,Sandip Sen

Häftad, Engelska, 1996

Del i serien Lecture Notes in Computer Science

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Beskrivning

This work is based on the workshop on adaptation and learning in multi-agent systems, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. The papers describe and analyze, both experimentally and theoretically, new learning and adaption approaches for situations in which several agents have to co-operate or compete. Also included, and aimed at the novice reader, are a comprehensive introductory survey on the areas with 154 references listed and a subject index.

Produktinformation

Utgivningsdatum:1996-02-27
Mått:155 x 235 x 15 mm
Vikt:394 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:568
Upplaga:1996
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783540609230

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Adaptation and learning in multi-agent systems: Some remarks and a bibliography.- Refinement in agent groups.- Opponent modeling in multi-agent systems.- A multi-agent environment for department of defense distribution.- Mutually supervised learning in multiagent systems.- A framework for distributed reinforcement learning.- Evolving behavioral strategies in predators and prey.- To learn or not to learn .......- A user-adaptive interface agency for interaction with a virtual environment.- Learning in multi-robot systems.- Learn your opponent's strategy (in polynomial time)!.- Learning to reduce communication cost on task negotiation among multiple autonomous mobile robots.- On multiagent Q-learning in a semi-competitive domain.- Using reciprocity to adapt to others.- Multiagent coordination with learning classifier systems.